方法对比

	Destination Net Promoter Analysis	Hospitality eWOM Analysis
领域	Tourism	Tourism
方法族	Process / pipeline	Process / pipeline
起源年份	2003	2008
提出者	Frederick Reichheld (Net Promoter Score); adapted to destination advocacy	Stephen Litvin, Ronald Goldsmith & Bing Pan
类型	Single-item recommendation-likelihood metric and advocacy-segmentation pipeline	Framework and pipeline for measuring electronic word-of-mouth volume, valence and influence
开创性文献	Reichheld, F. F. (2003). The One Number You Need to Grow. Harvard Business Review, 81(12), 46-54.	Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic Word-of-Mouth in Hospitality and Tourism Management. Tourism Management, 29(3), 458-468.
别名	Destination Advocacy Score, Destination Recommendation Index, Tourist Net Promoter Measurement, Destination Word-of-Mouth Likelihood Score	Electronic Word-of-Mouth Analysis, Online Review Influence Analysis, Hospitality Online WOM Measurement, Digital Word-of-Mouth Analytics
相关	4	4
摘要	Destination net promoter analysis adapts the Net Promoter Score, introduced by Frederick Reichheld (2003), to the measurement of destination advocacy. It rests on a single survey question, how likely a visitor is, on a 0-to-10 scale, to recommend the destination to a friend or colleague, and converts the answers into a compact indicator of word-of-mouth potential. Respondents are sorted into promoters, passives and detractors, and the score is the percentage of promoters minus the percentage of detractors. The metric is attractive for destinations because, as Litvin, Goldsmith and Pan (2008) emphasise, word-of-mouth is one of the most influential information sources in tourism, where intangible products are hard to judge before consumption; a destination's promoters become its advocates, spreading recommendations that drive future visitation, especially through electronic word-of-mouth.	Hospitality eWOM analysis is the systematic study of electronic word-of-mouth, the consumer-generated reviews, ratings, posts and comments that travellers share online about hotels, restaurants, attractions and destinations. Litvin, Goldsmith and Pan (2008) set out the foundational framework, defining eWOM, classifying its channels by communication scope and level of interactivity, and explaining why it matters so much in hospitality and tourism, whose intangible products are difficult to evaluate before consumption and are therefore judged heavily through the experiences of others. The analysis treats this online word-of-mouth as data, measuring its volume, its valence (how positive or negative it is) and the experience dimensions it reveals, and links these to outcomes such as bookings, satisfaction and reputation. Xiang and colleagues (2015) showed how large-scale text analytics of guest-generated reviews can deconstruct the hotel experience and connect it to satisfaction.